Abstract: A cascade circuit can include: N power conversion units connected in series between two ports of a power supply, where N is a positive integer greater than or equal to 2; a controller connected to one of the N power conversion units, and being configured to send a signal to be transmitted through the connected power conversion unit; where each of the power conversion units is configured to send the signal to be transmitted to a next-stage power conversion unit when the each of the power conversion unit shares a reference voltage with the adjacent next-stage power conversion unit; and where the signal to be transmitted is controlled to be transmitted from a previous-stage power conversion unit to a next-stage power conversion unit in sequence until the signal to be transmitted is received by all of the N power conversion units.

Abstract: A plurality of light sources placed at one end of a surface imaging system may generate and direct light rays to be incident onto a surface to be detected at high incident angles that are greater than or equal to a predetermined angle threshold, the predetermined angle threshold may be set to ensure that images of the surface to be detected that have at least a predetermined degree of contrast are to be obtained. An image sensor that is placed at another end of the surface imaging system may collect light rays reflected from the surface to be detected to form a first image of the surface to be detected.

Abstract: A method and apparatus for generating a virtual character, an electronic device and a computer readable storage medium are provided. The method includes: performing mesh simplification on an initial model of a virtual character to obtain a mesh-simplified model; obtaining a first target model by performing white model mapping rendering on an area of each material type on the mesh-simplified model, and obtaining a second target model by performing hyper-realistic rendering on the area of each material type on the mesh-simplified model; and establishing a bidirectional mapping between the first target model and the second target model, and obtaining a target virtual character through iterative updating of the bidirectional mapping.

Abstract: The present disclosure provides a video processing method, an apparatus, a device and a storage medium. The method includes: after determining a target effect style and determining a target video clip based on presentation of a video to be processed on a timeline, establishing a binding relationship between the target effect style and the target video clip in response to an effect application trigger operation, so as to achieve an effect of applying the target effect style to the target video clip. The embodiment of the present disclosure, by establishing the binding relationship between the target effect style and the target video clip, achieves the effect of effect processing only on a certain video clip of the video, thereby meeting the user's demand of effect processing only on a certain video clip, which increases flexibility of video effect processing, and further improves the user's experience of video effect processing.

Abstract: The invention relates to a composite motion robot based on springtail movement mechanism, which includes a body, a jumping mechanism, a balance wheel and a control module. The body includes a right pallet, a U-shaped frame, a curved slide, a casing, a fixing plate, a left pallet and a pin block; the control module is installed on the body. Based on springtail jumping motion mechanism and by setting the jumping mechanism and the balance wheel, the invention enables the robot to have capability of movement, such as jumping over obstacles, balance wheeled translation, flipping posture reset, and self-balance resetting which is otherwise difficult to be achieved by traditional balancing carts, etc.

Abstract: A method, apparatus, device, and storage medium for transforming a hairstyle are provided. The method may include: determining a face bounding box according to information on face key points of acquired face image; constructing grids according to the face bounding box; deforming, by using an acquired target hairstyle function, edge lines of at least a part of the constructed grids, which comprises the hairstyle, to obtain a deformed grid curve; determining a deformed hairstyle in the face image according to the deformed grid curve.

Abstract: Embodiments of the present disclosure provide a device waking-up method. The device waking-up method includes: a Bluetooth module receives data to be processed sent by a first Bluetooth peripheral when a protocol stack module is in a dormant state, where the Bluetooth module stores information, sent by the protocol stack module before entering the dormant state, of a second Bluetooth peripheral which successfully performs Bluetooth pairing with the Bluetooth module; and the Bluetooth module wakes up a device according to the data to be processed and the information of the second Bluetooth peripheral.

Abstract: A three-dimensional model processing method, an electronic device, and a storage medium are provided, which are related to fields of deep learning, augmented reality, and the like. The specific implementation includes: generating a target virtual three-dimensional model based on a target model template; generating a target picture based on graphic and textual information and a preset network; and determining a superposition processing result of the target virtual three-dimensional model based on the target virtual three-dimensional model and the target picture.

Abstract: A switching power circuit for charging a battery can include: four switches extending between two ports of a low-frequency AC input voltage and an energy storage circuit, where the energy storage circuit and a primary winding of a transformer are coupled between first and second nodes, the first node is a common node of the first and second switches, and the second node is a common node of the third and fourth switches; a rectification circuit having an input terminal coupled to a secondary winding of the transformer; a DC-DC converter having an input terminal coupled to an output terminal of the rectification circuit, and generates a charging current; and a control circuit that adjusts the charging current by controlling an operation of the DC-DC converter according to a charging requirement, in order to make an average value of the charging current meet the charging requirement.

Abstract: The present disclosure provides a video data processing method and device, and a readable storage medium, where the technical means is adopted which includes: processing, according to a preset trained deep learning algorithm model, input video data to be processed, to obtain a label vector of the video data; determining, according to a label vector of each music data in a music library and a preset recommendation algorithm, a recommendation score of the label vector of each music data with respect to the label vector of the video data; and taking, according to the each recommendation score, the music data matching the video data as background music. By means of the above, and further a deep learning algorithm model and a recommendation algorithm, the data processing efficiency of finding the background music of the video data in the music library is effectively improved, and the labor cost is reduced.

Abstract: The present disclosure provides a method for training an image editing model, a method for editing an image, apparatuses, a device, a storage medium and a computer program. An implementation plan is: acquiring a training sample set; and performing training steps as follows: selecting a description text sample and an image sample from the training sample set; determining a text direction vector based on the selected description text sample and a predetermined text template; inputting the text direction vector into a mapping network of the image editing model to obtain a bias vector; determining an image direction vector based on the selected image sample and the bias vector; calculating a loss value based on the text direction vector and the image direction vector; and determining, in response to the loss value meeting a threshold condition, that training of the image editing model is completed.

Abstract: A battery charging circuit can include: a primary rectifier circuit configured to rectify an input AC voltage into a rectified voltage signal; a DC-DC converter configured to generate a charging current according to the rectified voltage signal, in order to charge a battery; a control circuit configured to adjust the charging current by controlling an operation state of the DC-DC converter according to a charging requirement, in order to make an average value of the charging current meet the charging requirement; and where the charging current is controlled to be zero when an absolute value of the input AC voltage is lower than a predetermined threshold.

Abstract: Systems and techniques for end-to-end fuzzy entity matching are described herein. A first input and a second input may be received. The first input and the second input may be evaluated to identify common attribute types. A set of attribute entity matching models may be selected that correspond to the attribute types. The first input and the second input may be evaluated using the set of attribute entity matching models to determine a set of weighted scores for attribute pairs in the first input and the second input. The set of weighted scores may be evaluated using a table-level entity matching model to identify a common entity included in the first input and the second input. A linking dataset may be generated that includes a cross-linking facility indicating a relationship between a first entity descriptor in the first input and a second entity descriptor in the second input.

Abstract: An image processing method, an electronic device and a computer storage medium are provided, which relates to the fields of computer vision, augmented reality and artificial intelligence technologies. An implementation includes: acquiring a to-be-processed face image; reconstructing a face based on the to-be-processed face image to obtain a first blend coefficient vector based on a first blendshape base group; mapping the first blend coefficient vector to a second blendshape base group according to a pre-obtained coefficient mapping matrix between the first blendshape base group and the second blendshape base group to obtain a second blend coefficient vector based on the second blendshape base group; acquiring input face adjustment information, the face adjustment information including second blendshape base information; and obtaining a target face image based on the second blendshape base information and the second blend coefficient vector.

Abstract: The present disclosure provides a virtual image generation method and apparatus, an electronic device and a storage medium, and relates to the field of artificial intelligence technologies such as augmented reality, computer vision and deep learning. A specific implementation scheme involves: acquiring base coefficients corresponding to key points of a target face based on a target face picture; generating a structure of a virtual image of the target face based on a mapping relationship of spatial alignment between a preset virtual model and a standard model, a base of the standard model and the base coefficients corresponding to the key points of the target face; and performing texture filling on the structure of the virtual image based on textures of the target face picture, to obtain the virtual image of the target face.

Abstract: Provided are a computer program product, system, and method for using a machine learning module to rank technical solutions to user described technical problems to provide to a user. A solutions database is searched to determine a result set of answer files having keywords related to keywords of a technical problem in a user description. The result set of answer files, the user description of the technical problem, user profile information, and technical specifications of the computing system are provided as input to a machine learning module. The machine learning module outputs ranks of the answer files in the result set. A subset of answer files in the result set is selected based on ranks of the answer files in the result set and returned to the user.

Abstract: Provided are a power supply conversion device and a charging control method. The device includes: a transformer; a first rectifier circuit connected to a primary winding of the transformer used for converting a received alternating current into a first direct current, a voltage value of the first direct current being a first direct-current voltage, and the transformer used for converting the first direct-current voltage into a second direct-current voltage; a voltage converter connected to a secondary winding of the transformer and used for converting the second direct-current voltage to output a constant direct-current voltage or a pulsating direct-current voltage; and a controller connected to the first rectifier circuit and the voltage converter and used for controlling the voltage converter to selectably output the constant direct-current voltage or the pulsating direct-current voltage according to a desired charging mode of a device to be charged connected to the power supply conversion device.

Abstract: A method and apparatus for training a virtual image generating model, a method and apparatus for generating a virtual image, a device, a storage medium, and a computer program product are provided. The method for training a virtual image generating model includes: training a first initial model using a standard image sample set and a random vector sample set as first of sample data, to obtain an image generating model; training a second initial model using a test latent vector sample set and a test image sample set as second sample data, to obtain an image encoding model; training a third initial model using a standard image sample set and a descriptive text sample set as third sample data, to obtain an image editing model; and training a fourth initial model using the third sample data based on the above models, to obtain the virtual image generating model.

Abstract: Provided herein are methods, processes and apparatuses for non-invasive assessment of genetic variations that make use of decision analyses. The decision analyses sometimes include segmentation analyses and/or odds ratio analyses.

Abstract: The present application discloses a virtual object driving method, an apparatus, an electronic device and a readable storage medium, which relate to technical fields of artificial intelligence and deep learning. A specific implementing solution is as follows: obtaining a target image of a real object acquired by a camera when the real object makes a limb movement; inputting the target image into a coordinate acquisition model to obtain coordinates of a plurality of key points on a limb of the real object; determining a posture of the limb of the real object according to coordinates of each key point; driving, according to the posture of the real object, a virtual object displayed on a screen to present the limb movement of the real object. The method greatly reduces operation complexity and cost consumption when driving a virtual image.